{"title":"考虑到依赖性和不确定性,多源信息融合用于复杂项目的安全风险评估。","authors":"Kai Guo, Limao Zhang","doi":"10.1111/risa.17651","DOIUrl":null,"url":null,"abstract":"<p><p>The success of tunneling projects is crucial for infrastructure development. However, the potential leakage risk is particularly challenging due to the inherent uncertainties and fuzziness involved. To address this demanding challenge, a hybrid approach integrating the copula theory, cloud model, and risk matrix, is proposed. The dependence of multiple risk-related influential factors is explored by the construct of the copula-cloud model, and the diverse information is fused by applying the risk matrix to gain a crisp risk result. A case study is performed to test the applicability of the proposed approach, in which a risk index system consisting of nine critical factors is developed and Sobol-enabled global sensitivity analysis (GSA) is incorporated to investigate the contributions of different factors to the risk magnitude. Key findings are as follows: (1) Risk statuses of the studied three tunnel sections are perceived as under grade I (safe), II (low-risk), and III (medium-risk), respectively, and the waterproof material aspect is found prone to deteriorating the tunnel sections. Furthermore, the proposed approach allows for a better understanding of the trends in the risk statuses of the tunnel sections. (2) Strong interactions between influential factors exist and exert impacts on the final risk results, proving the necessity of studying the factor dependence. (3) The developed neutral risk matrix presents a strong robustness and displays a higher recognition capacity in risk assessment. The novelty of this research lies in the consideration of the dependence and uncertainty in multisource information fusion with a hybrid copula-cloud model, enabling to perform a robust risk assessment under different risk matrices with varying degrees of risk tolerance.</p>","PeriodicalId":21472,"journal":{"name":"Risk Analysis","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multisource information fusion for safety risk assessment in complex projects considering dependence and uncertainty.\",\"authors\":\"Kai Guo, Limao Zhang\",\"doi\":\"10.1111/risa.17651\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The success of tunneling projects is crucial for infrastructure development. However, the potential leakage risk is particularly challenging due to the inherent uncertainties and fuzziness involved. To address this demanding challenge, a hybrid approach integrating the copula theory, cloud model, and risk matrix, is proposed. The dependence of multiple risk-related influential factors is explored by the construct of the copula-cloud model, and the diverse information is fused by applying the risk matrix to gain a crisp risk result. A case study is performed to test the applicability of the proposed approach, in which a risk index system consisting of nine critical factors is developed and Sobol-enabled global sensitivity analysis (GSA) is incorporated to investigate the contributions of different factors to the risk magnitude. Key findings are as follows: (1) Risk statuses of the studied three tunnel sections are perceived as under grade I (safe), II (low-risk), and III (medium-risk), respectively, and the waterproof material aspect is found prone to deteriorating the tunnel sections. Furthermore, the proposed approach allows for a better understanding of the trends in the risk statuses of the tunnel sections. (2) Strong interactions between influential factors exist and exert impacts on the final risk results, proving the necessity of studying the factor dependence. (3) The developed neutral risk matrix presents a strong robustness and displays a higher recognition capacity in risk assessment. The novelty of this research lies in the consideration of the dependence and uncertainty in multisource information fusion with a hybrid copula-cloud model, enabling to perform a robust risk assessment under different risk matrices with varying degrees of risk tolerance.</p>\",\"PeriodicalId\":21472,\"journal\":{\"name\":\"Risk Analysis\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Risk Analysis\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/risa.17651\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Risk Analysis","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/risa.17651","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
摘要
隧道工程的成功对于基础设施的发展至关重要。然而,由于其固有的不确定性和模糊性,潜在的渗漏风险尤其具有挑战性。为了应对这一严峻挑战,我们提出了一种融合了 copula 理论、云模型和风险矩阵的混合方法。通过共轭云模型的构建,探索了多种风险相关影响因素的依赖关系,并通过应用风险矩阵将各种信息融合在一起,从而获得清晰的风险结果。通过案例研究检验了所提方法的适用性,其中开发了一个由九个关键因素组成的风险指标体系,并结合索博尔全局敏感性分析(GSA)来研究不同因素对风险大小的贡献。主要结论如下(1) 所研究的三个隧道断面的风险状况分别被视为 I 级(安全)、II 级(低风险)和 III 级(中风险),并且发现防水材料方面容易导致隧道断面恶化。此外,所提出的方法还有助于更好地了解隧道断面风险状况的变化趋势。(2)影响因素之间存在强烈的相互作用,并对最终风险结果产生影响,这证明了研究因素依赖性的必要性。(3) 所开发的中性风险矩阵具有很强的稳健性,在风险评估中表现出较高的识别能力。本研究的新颖之处在于利用混合共云模型考虑了多源信息融合中的依赖性和不确定性,从而能够在不同风险矩阵下以不同的风险容忍度进行稳健的风险评估。
Multisource information fusion for safety risk assessment in complex projects considering dependence and uncertainty.
The success of tunneling projects is crucial for infrastructure development. However, the potential leakage risk is particularly challenging due to the inherent uncertainties and fuzziness involved. To address this demanding challenge, a hybrid approach integrating the copula theory, cloud model, and risk matrix, is proposed. The dependence of multiple risk-related influential factors is explored by the construct of the copula-cloud model, and the diverse information is fused by applying the risk matrix to gain a crisp risk result. A case study is performed to test the applicability of the proposed approach, in which a risk index system consisting of nine critical factors is developed and Sobol-enabled global sensitivity analysis (GSA) is incorporated to investigate the contributions of different factors to the risk magnitude. Key findings are as follows: (1) Risk statuses of the studied three tunnel sections are perceived as under grade I (safe), II (low-risk), and III (medium-risk), respectively, and the waterproof material aspect is found prone to deteriorating the tunnel sections. Furthermore, the proposed approach allows for a better understanding of the trends in the risk statuses of the tunnel sections. (2) Strong interactions between influential factors exist and exert impacts on the final risk results, proving the necessity of studying the factor dependence. (3) The developed neutral risk matrix presents a strong robustness and displays a higher recognition capacity in risk assessment. The novelty of this research lies in the consideration of the dependence and uncertainty in multisource information fusion with a hybrid copula-cloud model, enabling to perform a robust risk assessment under different risk matrices with varying degrees of risk tolerance.
期刊介绍:
Published on behalf of the Society for Risk Analysis, Risk Analysis is ranked among the top 10 journals in the ISI Journal Citation Reports under the social sciences, mathematical methods category, and provides a focal point for new developments in the field of risk analysis. This international peer-reviewed journal is committed to publishing critical empirical research and commentaries dealing with risk issues. The topics covered include:
• Human health and safety risks
• Microbial risks
• Engineering
• Mathematical modeling
• Risk characterization
• Risk communication
• Risk management and decision-making
• Risk perception, acceptability, and ethics
• Laws and regulatory policy
• Ecological risks.